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Found 31 result(s)
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BioChem is an archive of marine biological and chemical data maintained by Fisheries and Oceans Canada (DFO). It holds biological and chemical data that are: from department research initiatives and collected in areas of Canadian interest
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The Alcohol and Gaming Commission of Ontario’s Data Inventory lists all of the agency’s data sets and identifies whether a data set is currently open, in the process of being opened or exempt from being released as open data due to legal, security, privacy, confidentiality or commercially-sensitive reasons.
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The Alberta Food Composition Database (AFCDB) is the first comprehensive resource on food constituents, chemistry and biology dedicated to major Alberta-grown produce. It provides information on both macronutrients and micronutrients, including many of the constituents that give foods their flavor, color, taste, texture and aroma. Users can view the contents of the AFCDB from the “FoodView” (listing foods by their chemical composition) or the “ChemView” (listing chemicals by their food sources).
<<<!!!<<<The repository is no longer available <<<!!!<<< TOXNET has moved. Most content will continue to be collected and reviewed; selected information is accessible through PubChem, PubMed, and Bookshelf. If you have questions, please contact NLM Customer Support at https://support.nlm.nih.gov/ >>>!!!>>>
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
M-CSA is a database of enzyme reaction mechanisms. It provides annotation on the protein, catalytic residues, cofactors, and the reaction mechanisms of hundreds of enzymes. There are two kinds of entries in M-CSA. 'Detailed mechanism' entries are more complete and show the individual chemical steps of the mechanism as schemes with electron flow arrows. 'Catalytic Site' entries annotate the catalytic residues necessary for the reaction, but do not show the mechanism. The M-CSA (Mechanism and Catalytic Site Atlas) represents a unified resource that combines the data in both MACiE and the CSA
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coastMap offers campaign data, model analysis and thematic maps predominantly in the Biogeosciences. Spotlights explain in a nutshell important topics of the research conducted for the interested public. The portal offers applications to visualise and download field and laboratory work and to connect the information with interactive maps. Filter functions allow the user to search for general topics like a marine field of interest or single criteria, for example a specific ship campaign or one of 1000 measured parameters.
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Plastics are widely used in our economy and each year, at least 350-400 million tons are being produced at a global level. Due to poor recycling and low circular use, tens of millions of tons accumulate annually in marine and terrestrial environments. While it has become obvious that micro and macroplastics contaminate our environments recent research has identified few bacteria and fungi actively degrading plastics by enzymatic reactions. In general these are promiscuous enzymes (hydrolases) acting on low crystaline and mostly low density polymers of PET, ester-based PUR and oligomers of PA. Notably today, no enzymes have been characterized on a biochemical level for polymeric and crystaline PE, ether-based PUR, PS, PVC, PP. While many publications report on plastic degradation often, no convincing biochemical data have been published. Therefore the PAZy database lists exclusively biochemically characterized plastic-active enzymes. Predicted and putative enzymes that were not characterized on a biochemical, functional or structural level are not included in the PAZy database. The entries are manually curated.
GRID-Geneva is a unique platform providing analyses and solutions for a wide range of environmental issues. GRID-Geneva serves primarily the needs of its three institutional partners - UNEP, the Swiss Federal Office for the Environment (FOEN) and the University of Geneva (UniGe) - which are linked by an ongoing, multi-year “Partnership Agreement”, along with other local-to-global stakeholders. GRID-Geneva is also a bilingual English and French centre and the key francophone link within the global GRID network of centres. GRID-Geneva is a key centre of geo-spatial know-how, with strengths in GIS, IP/remote sensing and statistical analyses, integrated through modern spatial data infrastructures and web applications. Working at the interface between scientific information and policy/decision-making, GRID-Geneva also helps to develop capacities in these fields of expertise among target audiences, countries and other groups.
Content type(s)
CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.
The repository is no longer available. <<<!!!<<< CCRIS information is migrated to PubChem (https://www.ncbi.nlm.nih.gov/pcsubstance?term=%22Chemical%20Carcinogenesis%20Research%20Information%20System%20(CCRIS)%22%5BSourceName%5D%20AND%20hasnohold%5Bfilt%5D) Help for CCRIS Users in PubChem: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.html or PDF: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.pdf. >>>!!!>>>
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The Research Data Center of the Federal Institute for Occupational Safety and Health (FDZ-BAuA) provides selected data from BAuA research. The Public Use Files can be used by scientists as well as by the interested public.
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The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education.
The UCD Digital Library is a platform for exploring cultural heritage, engaging with digital scholarship, and accessing research data. The UCD Digital Library allows you to search, browse and explore a growing collection of historical materials, photographs, art, interviews, letters, and other exciting content, that have been digitised and made freely available.
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The Yeast Metabolome Database (YMDB) is a manually curated database of small molecule metabolites found in or produced by Saccharomyces cerevisiae (also known as Baker’s yeast and Brewer’s yeast). This database covers metabolites described in textbooks, scientific journals, metabolic reconstructions and other electronic databases.
The Comparative RNA Web (CRW) Site disseminates information about RNA structure and evolution that has been determined using comparative sequence analysis. We present both raw (sequences, structure models, metadata) and processed (analyses, evolution, accuracy) data, organized into four main sections.
PSnpBind is a large database of protein–ligand complexes covering a wide range of binding pocket mutations and small molecules’ landscape. This database can be used as a source of data for different types of studies, for example, developing machine learning algorithms to predict protein–ligand affinity or mutation's effect on it which requires an extensive amount of data with a wide coverage of mutation types and small molecules. Also, studies of protein-ligand interactions and conformer orientation changes across different mutated versions of a protein can be established using data from PSnpBind.